6 citations · 10 across the 2 of their papers we have counts for
2 papers
cs.CR2022★ 6 cited
Medha: Microcoded Hardware Accelerator for computing on Encrypted Data
Ahmet Can Mert, Aikata, Sunmin Kwon +4
Homomorphic encryption (HE) enables computation on encrypted data, and hence it has a great potential in privacy-preserving outsourcing of computations to the cloud. Hardware accel…
cs.LG2021★ 4 cited
Privacy-Preserving Machine Learning with Fully Homomorphic Encryption for Deep Neural Network
Joon-Woo Lee, HyungChul Kang, Yongwoo Lee +8
Fully homomorphic encryption (FHE) is one of the prospective tools for privacypreserving machine learning (PPML), and several PPML models have been proposed based on various FHE sc…